SEER : A Knapsack approach to Exemplar Selection for In-Context HybridQA
- URL: http://arxiv.org/abs/2310.06675v2
- Date: Fri, 20 Oct 2023 08:02:25 GMT
- Title: SEER : A Knapsack approach to Exemplar Selection for In-Context HybridQA
- Authors: Jonathan Tonglet, Manon Reusens, Philipp Borchert, Bart Baesens
- Abstract summary: In this work, we present Selection of Exmplars for hybrid Reasoning (SEER), a novel method for selecting a set of exemplars that is both representative and diverse.
The effectiveness of SEER is demonstrated on FinQA and TAT-QA, two real-world benchmarks for HybridQA, where it outperforms previous exemplar selection methods.
- Score: 1.0323063834827413
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Question answering over hybrid contexts is a complex task, which requires the
combination of information extracted from unstructured texts and structured
tables in various ways. Recently, In-Context Learning demonstrated significant
performance advances for reasoning tasks. In this paradigm, a large language
model performs predictions based on a small set of supporting exemplars. The
performance of In-Context Learning depends heavily on the selection procedure
of the supporting exemplars, particularly in the case of HybridQA, where
considering the diversity of reasoning chains and the large size of the hybrid
contexts becomes crucial. In this work, we present Selection of ExEmplars for
hybrid Reasoning (SEER), a novel method for selecting a set of exemplars that
is both representative and diverse. The key novelty of SEER is that it
formulates exemplar selection as a Knapsack Integer Linear Program. The
Knapsack framework provides the flexibility to incorporate diversity
constraints that prioritize exemplars with desirable attributes, and capacity
constraints that ensure that the prompt size respects the provided capacity
budgets. The effectiveness of SEER is demonstrated on FinQA and TAT-QA, two
real-world benchmarks for HybridQA, where it outperforms previous exemplar
selection methods.
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